Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 2,881 to 2,890 of 168,134 articles

Beyond the Leaderboard: Rethinking Medical Benchmarks for Large Language Models

arXiv
Large language models (LLMs) show significant potential in healthcare, prompting numerous benchmarks to evaluate their capabilities. However, concerns persist regarding the reliability of these benchmarks, which often lack clinical fidelity, robust... read more 

Small Lesions-aware Bidirectional Multimodal Multiscale Fusion Network for Lung Disease Classification

arXiv
The diagnosis of medical diseases faces challenges such as the misdiagnosis of small lesions. Deep learning, particularly multimodal approaches, has shown great potential in the field of medical disease diagnosis. However, the differences in dimens... read more 

Do Recommender Systems Really Leverage Multimodal Content? A Comprehensive Analysis on Multimodal Representations for Recommendation

arXiv
Multimodal Recommender Systems aim to improve recommendation accuracy by integrating heterogeneous content, such as images and textual metadata. While effective, it remains unclear whether their gains stem from true multimodal understanding or incr... read more 

Stakeholder Perspectives on Trustworthy AI for Parkinson Disease Management Using a Cocreation Approach: Qualitative Exploratory Study.

Journal of medical Internet research
BACKGROUND: Parkinson disease (PD) is the fastest-growing neurodegenerative disorder in the world, with prevalence expected to exceed 12 million by 2040, which poses significant health care and societal challenges. Artificial intelligence (AI) system... read more 

Beyond the type 1 pattern: comprehensive risk stratification in Brugada syndrome.

Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing
Brugada Syndrome (BrS) is an inherited cardiac ion channelopathy associated with an elevated risk of sudden cardiac death, particularly due to ventricular arrhythmias in structurally normal hearts. Affecting approximately 1 in 2,000 individuals, BrS ... read more 

Transductive zero-shot learning via knowledge graph and graph convolutional networks.

Scientific reports
Zero-shot learning methods are used to recognize objects of unseen categories. By transferring knowledge from the seen classes to describe the unseen classes, deep learning models can recognize unseen categories. However, relying solely on a small la... read more 

PEYOLO a perception efficient network for multiscale surface defects detection.

Scientific reports
Steel defect detection is a crucial aspect of steel production and quality control. Therefore, focusing on small-scale defects in complex production environments remains a critical challenge. To address this issue, we propose an innovative perception... read more 

Continual Multiple Instance Learning for Hematologic Disease Diagnosis

arXiv
The dynamic environment of laboratories and clinics, with streams of data arriving on a daily basis, requires regular updates of trained machine learning models for consistent performance. Continual learning is supposed to help train models without... read more 

Comparison of machine learning models for mucopolysaccharidosis early diagnosis using UAE medical records.

Scientific reports
Rare diseases, such as Mucopolysaccharidosis (MPS), present significant challenges to the healthcare system. Some of the most critical challenges are the delay and the lack of accurate disease diagnosis. Early diagnosis of MPS is crucial, as it has t... read more 

Transformer-Based Deep Learning Approaches for Speech-Based Dementia Detection: A Systematic Review.

IEEE journal of biomedical and health informatics
As the population of older adults continues growing, so will the need for cost-effective approaches to early dementia detection. Deep learning approaches using patient speech samples show promising results. This systematic review examines studies uti... read more